From Black Box to Trusted, Actionable Intelligence
Empower enterprises to build explainable, certifiable, and actionable AI systems based on deep learning.
Xpdeep first explains the model itself — before any prediction. Because you cannot improve or optimize what you don't understand and measure.
Explanations are generated inside the model — not approximated after the fact.
By first explaining the model itself, Xpdeep exposes its blind spots and strengths, building a foundation for predictions that come with real-time explanations and "how-to improve" insights.
ROI — The Unsuspected Business Impact of Explainability
Enterprises dramatically underestimate the impact of explainability. Discover how transparent and certifiable deep learning unlocks savings, innovation, and growth that black-box AI cannot deliver.
Backed by the EU (Chips JU) • Adopted by leaders in automotive, technology & defense
The Black Box Barrier
Why high-performing models fail to reach production.
Countless teams have dreamed of deploying deep learning models for virtual sensors, process optimization, autonomous systems, and now LLMs. Yet, too many initiatives are stopped cold by compliance and risk management issues due to the black box nature of AI.
Self-explainability changes all that.
By replacing opaque decision-making with transparent, ante-hoc architecture, Xpdeep turns "risky" innovation into trusted, deployable assets.
Aligned Performance, Measurable ROI
Explainability delivers measurable impact at every level of the enterprise.
With Xpdeep, AI becomes not only transparent and certifiable — but also a direct driver of savings, innovation, and growth.
AI ROI — Smarter, Faster, Frugal
Build models that require fewer inputs, train faster, and are certifiable by design. Explainability helps identify the most relevant data, shorten design cycles, and simplify compliance — turning AI development into a repeatable, efficient process.
Savings ROI — Explainability That Cuts Costs
Deploy explainable AI to reduce sensor count, simplify industrial systems, and optimize maintenance or production processes. With virtual sensing, explainable predictions, and prescriptive insights, Xpdeep helps enterprises redesign equipment and operations for cost, energy, and material efficiency.
Want deeper examples of how explainability reduces component costs, engineering cycles, and operational inefficiencies across critical industries?
Learn more →Growth ROI — Explainability That Creates Value
Unlock new revenue streams and customer experiences powered by trustable AI. From adaptive comfort systems and energy-aware control modules to transparent claim handling or personalized pricing, Xpdeep enables new features and services that were once too risky to deploy.
Explore how explainable deep models enable adaptive products, premium services, personalization, and trusted decision systems in regulated industries.
Learn more →Ready to See Real ROI Impact?
Build or Explain — the Fastest Path to Trusted AI
Xpdeep lets you either create new self-explainable models or reconstruct the explainability of existing ones.
Both paths give you transparent, certifiable, and production-ready AI — designed for teams that need trust before deployment.
Build a Powerful Trustworthy Deep Model
Build, optimize, and explain with Xpdeep.
Access the full self-explainable deep learning framework — including XpViz, XpAct, and XpComply — available as a SaaS with a freemium entry plan.
Ideal for enterprises and partners who want to create or test explainable models.
Access requires validation by our sales team. Partners can start up to three customer projects freely.
Add self-explainability to your existing deep models.
Transform your trained models into transparent and certifiable AI systems.
Upload your PyTorch model and Xpdeep reconstructs its full internal logic — revealing decision paths, exposing weaknesses, generating audit-ready documentation, and making every prediction explainable. Your existing models become governed, deployable, and compliant without retraining.
Access requires validation by our sales team.
Ante-Hoc. No Post-Hoc. Real Explainability.
Xpdeep is the first ante-hoc, self-explainable deep learning framework. Models explain themselves from the inside — no approximations, no after-the-fact patches. This foundation enables trusted, certifiable, and actionable intelligence at every step of the lifecycle.
Why Ante-Hoc Explainability Changes Everything
Post-hoc explainability attempts to interpret a black-box model after it's trained.
Xpdeep takes the opposite approach: explainability is built into the model's internal structure from the start.
This ante-hoc foundation enables:
- Reliable optimization of deep models, grounded in their real internal logic
- Actionable intelligence, not guesswork
- Audit-ready explanations aligned with regulatory needs
- Faster certification for mission-critical and regulated applications
- A direct path from insight → action, thanks to XpViz our visual benchmark for AI teams, XpComply for compliance and risk management departments, and XpAct for users
Not Another Monitoring Tool. Not Another XAI Add-On.
Most solutions explain black-box models after they are built (post-hoc) or monitor them after they are deployed (observability).
Xpdeep is different:
It is a full deep learning framework with ante-hoc explainability built in.
Post-Hoc XAI
Approximates explanations after training
AI Observability
Monitors errors after deployment
Xpdeep
Builds models that are transparent by design, enabling optimization, certification, and real-world actionability
Why Now: Regulation, Risk & ROI Are Reshaping AI
Trust Gap
Most AI projects still fail to reach production because teams cannot explain what their models do or why. Xpdeep first explains the model itself, revealing how it makes decisions and where it may fail. Each prediction is then mapped onto this decision graph — closing the trust gap between data science, business, and regulation.
Compliance
The EU AI Act and comparable regulations across sectors such as finance, healthcare, automotive, defense, etc. are reshaping AI governance worldwide. Organizations now require explainable, auditable systems able to justify decisions instantly. Xpdeep integrates compliance into every stage of the model lifecycle — certification by design, not by retrofit.
Risk Management
Organizations hesitate to deploy deep learning because they can't quantify the operational and compliance risks involved. Xpdeep introduces model-level risk assessment, allowing teams to identify, measure, and mitigate uncertainty — turning deep learning into a governed, deployable asset.
ROI Pressure
Proving ROI from AI is no longer about faster prototypes — it's about deployment. By making deep models explainable, certifiable, and risk-controlled, Xpdeep allows organizations to reinvent processes, products, and services with models they can finally trust in production.
Built for Critical & Regulated Environments
From cars to code to chemical plants, Xpdeep powers explainable and certifiable AI across Europe's most demanding industries. Our framework helps each sector turn deep learning into a trusted, auditable, and performance-driven asset.
Energy & Utilities
Optimize power generation and grid management with full traceability. Ensure compliance with ISO 50001 and NERC CIP.
Automotive
Accelerate the path to ISO 26262-ready AI. Predict quality, optimize manufacturing, and certify safety-critical models.
Aerospace & Defense
Gain explainability under mission pressure. Enable self-optimizing systems for detection, tracking, and maintenance.
Production Equipment
Make every machine smarter — and auditable. Embed self-explainable AI directly into industrial and semiconductor tools.
Process Industries
Optimize yield and energy with full transparency. Explain process variables, ensure compliance, and support operator trust.
Discrete Manufacturing
Reduce downtime and improve quality. Use counterfactual optimization to anticipate and prevent production issues.
BFSI
Turn regulatory burden into a competitive advantage. Ensure model fairness, governance, and explainable credit-risk models.
Healthcare & MedTech
Build AI that clinicians can trust. Deliver explainable, certifiable diagnostics that meet ISO 13485 and GDPR standards.
Explainability for Time-Series — Natively Built In
Most explainability tools fail when confronted with temporal data. Xpdeep is the first framework to offer native explainability for deep time-series models, allowing enterprises to understand when, how, and why predictions evolve over time.
Xpdeep is the only AI framework that explains the model before any prediction, using an ante-hoc, self-explainable deep learning architecture. This eliminates the approximations of post-hoc XAI and enables real, measurable, certifiable optimization. Every Xpdeep workflow begins with structural explainability — understanding and measuring the model's true internal logic before any prediction or improvement.
The Xpdeep Lifecycle — One Framework, Six Explainable Stages
Xpdeep's AI lifecycle is a six-step journey to trustworthy AI. It starts with Design, where explainability is built into your models and guides the selection of the right input variables — a key requirement in most regulations. Understand then evaluates the model's performance, strengths, and weaknesses such as false negatives and false positives. Optimize leverages explainability to identify improvement paths — from targeted retraining to guided data augmentation — because you can't optimize what you don't understand. Explain & Certify validates trust before deployment with automated documentation and regulatory readiness. Predict & Explain delivers real-time predictions with confidence intervals and explanations. Act delivers how-to, comparative, and other actionable analyses to achieve the desired outcomes. Explore each stage to see how explainability accelerates ROI.
Each stage of the lifecycle builds on Xpdeep's ante-hoc foundation: you cannot optimize, certify, or act on what you cannot understand. By revealing the true internal behavior of deep models, Xpdeep allows teams to move from black-box experimentation to trusted, actionable AI development.
- 1
1. Design
Explainability is built into your model from the start. Xpdeep helps identify and select the right variables using ante-hoc structural understanding — reducing noise, improving robustness, and aligning with regulatory expectations from day one.
Learn more - 2
2. Understand
Gain a complete view of the model's behavior using true internal explainability, not post-hoc approximations. Identify strengths, weaknesses, false positives, false negatives, and hidden dependencies using structural insight.
Learn more - 3
3. Optimize
Xpdeep turns understanding into improvement. Guided by ante-hoc transparency, teams perform targeted retraining, guided data augmentation, and variable reduction. Because you can't optimize what you don't understand.
Learn more - 4
4. Explain & Certify
Validate trust before deployment. Xpdeep generates documentation and reproducible analyses grounded in the model's true internal logic — supporting governance, quality assurance, and certification needs under frameworks such as the EU AI Act.
Learn more - 5
5. Predict & Explain
Every prediction is accompanied by its explanation. Xpdeep delivers real-time predictions with confidence intervals, sequence-aware reasoning, and 'how to improve' insights — ensuring outcomes remain transparent, controllable, and aligned with enterprise requirements.
Learn more - 6
6. Act
Turn insight into action. Xpdeep generates how-to, comparative, and goal-oriented analyses grounded in the model's internal pathways — enabling explainable decision-making within operational workflows.
Learn more
Why this lifecycle matters
Each step in the Xpdeep lifecycle bridges the gap between deep-learning performance and enterprise governance. By embedding ante-hoc explainability, auditability, and optimization into every phase, Xpdeep transforms AI from a black box into a certifiable, transparent, and actionable process.
From Black Box AI to Trusted, Actionable Intelligence.
One Core, Three Environments
The Xpdeep Platform connects AI, business, and compliance teams around a single core technology. It's not another explainability plugin — it's a fully integrated framework with three complementary environments that make deep learning accountable and actionable.
Understand first. Then act, optimize, and govern.
XpViz
For Data & AI Teams
Explore, understand, and improve your models. XpViz provides deep interpretability, fairness metrics, model comparison, and advanced visual analytics — helping teams understand model behavior and measure every improvement.
Built on an ante-hoc foundation — XpViz exposes the model's internal logic, enabling precise optimization rather than post-hoc guesses.
XpAct
For Business Teams
Connect AI insights to real-world KPIs. XpAct combines explainable predictions and prescriptions with an integrated LLM that interprets and comments on results — turning complex model insights into clear, actionable guidance.
Turn insights into actionable intelligence. Ante-hoc explainability ensures every recommended action is grounded in the real behavior of the model.
XpComply
For Risk & Compliance Teams
Govern, document, and certify your AI. XpComply automates reporting, fairness checks, and regulatory alignment — providing a shared workspace where compliance and technical teams speak the same language.
Ante-hoc transparency makes compliance simpler, faster, and audit-ready — no reverse-engineering of black-box models.
Explainability That Delivers ROI
By making models self-explainable from the inside, Xpdeep reduces variables, accelerates cycles, simplifies compliance, and unlocks new growth and optimization opportunities.
Explainability is not documentation — it is a lever for measurable business value.
AI ROI
Build smarter, faster, more frugal models
Savings ROI
Reduce costs through optimization and efficiency
Growth ROI
Unlock new revenue and market opportunities
Works Seamlessly with Your Stack
Xpdeep was built to integrate, not replace. It runs natively with PyTorch, plugs into existing MLOps pipelines (MLflow, Airflow, Kubernetes, Databricks…), and supports both training and inference workflows. Data scientists can keep their tools — and gain full transparency, compliance, and optimization capabilities within the same environment.
Models built or explained with Xpdeep can be deployed anywhere — on-prem, edge, or cloud — with traceability baked in. Every prediction and counterfactual analysis remains consistent across runs and environments, enabling industrial-grade governance and reproducibility.
Native PyTorch compatibility
API & SDK integration
Cloud / Edge / On-prem deployment
MLflow & Kubernetes ready
Partner with Xpdeep
Join a growing ecosystem of consulting firms, system integrators, and technology partners delivering explainable, certifiable, and production-ready AI to their clients.
As a partner, you gain access to dedicated resources, pre-built demo environments, and shared revenue opportunities across industries.
Ready to Deploy Trusted AI?
With No Post-Hoc and full ante-hoc explainability, Xpdeep provides transparent, certifiable, and actionable deep learning — ready for enterprise deployment.
Whether you need to explain an existing model or design a certifiable new one, Xpdeep makes deep learning ready for the real world — transparent, governed, and ROI-proven.